LlamaIndex

Health v2 · maintenance only

Adoption not part of the score

51883 stars · 8029 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LlamaIndex is a Python (with a TypeScript variant) framework for building LLM-powered applications, centered on ingesting, indexing, and querying documents for retrieval-augmented generation and document agents. It provides data connectors, vector store integrations, query engines, and multi-agent orchestration.

Use cases

• build a chatbot over my own documents
• index pdfs and query them with an llm
• build a rag pipeline with vector search
• create document agents that answer questions from files
• connect custom data sources to an llm
• fine-tune and evaluate llm applications
• build multi-agent workflows over enterprise data

When to choose

• you need retrieval-augmented generation over private or unstructured data
• you want many prebuilt data connectors and vector store integrations
• you are building document Q&A, agents, or chat over your knowledge base in Python or TypeScript

When to avoid

• you only need raw LLM API calls without retrieval or indexing
• you want a lightweight prompt library rather than a full data framework
• you need a non-Python/non-TypeScript runtime

Facets

framework · maturity stable

rag agent-framework llm-inference vector-database ocr data-science etl large-language-models machine-learning python cross-platform llamaindex document-indexing llm-framework data-connectors query-engines typescript retrieval-augmented-generation ai-agents natural-language-processing nodejs

Member repositories

For agents

markdown · JSON · MCP: product_card(name="run-llama/llama_index")